International audienceDynamic contrast agent enhanced ultrasound (DCEUS) is considered as a safe, noninvasive, accurate, and economic tool for analysing blood perfusion of various organs [1]. Gas-filled mi-crobubble contrast agents are used as intravascular flow tracers. In this study, a new methodology is proposed to quantify the divergence (i.e sources, sinks), curl (i.e sheering) and amplitude in the apparent microbubble transports during the bolus arrival. The efficiency of proposed methodology is evaluated in-vivo, for the classification of focal nodular hyperplasia (FNH) and inflammatory hepatic adenomas (I-HCA)

Denis De Senneville, Baudouin

Frulio, Nora

Lafitte, Luc

Laumonier, Hervé

Salut, Cécile

Trillaud, Hervé

English

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Submitted on 24 Nov 2019
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Hepatic tumor diagnosis by analysing dense transport
fields in contrast-enhanced ultrasound
Baudouin Denis de Senneville, Nora Frulio, Hervé Laumonier, Cécile Salut,
Luc Lafitte, Hervé Trillaud
To cite this version:
Baudouin Denis de Senneville, Nora Frulio, Hervé Laumonier, Cécile Salut, Luc Lafitte, et al.. Hepatic
tumor diagnosis by analysing dense transport fields in contrast-enhanced ultrasound. ISBI19 - 16th
IEEE International Symposium on Biomedical Imaging, Apr 2019, Venise, Italy. ￿hal-02377660￿
HEPATIC TUMOR DIAGNOSIS BY ANALYSING DENSE TRANSPORT FIELDS IN
CONTRAST-ENHANCED ULTRASOUND
B. Denis de Senneville? N. Frulio† H. Laumonier† C. Salut† L. Lafitte? H. Trillaud†,‡
? Mathematical Institute of Bordeaux, UMR 5251 CNRS/University of Bordeaux/INRIA, France
† Department of Diagnostic and Interventional Imaging, Hoˆpital Saint-Andre´,
Centre Hospitalier Universitaire de Bordeaux, †IMOTION, University of Bordeaux
ABSTRACT
Dynamic contrast agent enhanced ultrasound (DCEUS) is con-
sidered as a safe, noninvasive, accurate, and economic tool for
analysing blood perfusion of various organs [1]. Gas-filled mi-
crobubble contrast agents are used as intravascular flow tracers.
In this study, a new methodology is proposed to quantify the di-
vergence (i.e sources, sinks), curl (i.e sheering) and amplitude in
the apparent microbubble transports during the bolus arrival. The
efficiency of proposed methodology is evaluated in-vivo, for the
classification of focal nodular hyperplasia (FNH) and inflammatory
hepatic adenomas (I-HCA).
1. INTRODUCTION
The diagnosis between FNH and I-HCA is sometime difficult at
DCEUS because both demonstrate a hyper-enhancing at the arterial
phase with difficulties to differentiate the centrifugal or centripetal
filling of the tumor with only qualitative visual analysis.
Recent efforts in DCEUS aim at quantifying parameters related
to the ultrasound contrast enhancement in the vascular compartment
and at using these latter as indicators for several pathological condi-
tions. In particular, quantitative analysis with the use of a transport
equation has been recently introduced to estimate the apparent mi-
crobubble velocity of the bolus arrival [2]. In the current study, we
propose a new methodology designed to quantify the divergence (i.e
sources, sinks), curl (i.e sheering) and amplitude in the estimated
apparent dense transport field. The latter provide three very simple
indicators of displacement vector directions, orientations and mag-
nitude, which are used as inputs of a binary FNH/I-HCA classifier.
2. RESULTS
46 patients with FNH (n=29) or I-HCA (n=17) were analyzed
(histological diagnosis). Fig. 1 reports typical estimated microbub-
ble transport fields obtained for two DCEUS experiment (upper
row=FNH/ bottom row=I-HCA) 0.75 s after the microbubble arrival
time. The apparent flow field in 1b shows a fast centrifugal filling
of the lesion from a central vessel and radial vascular branches. On
the contrary, 1d shows a hyper-enhancing in the arterial phase with
an enhancement pattern beginning peripherally, with fast centripetal
filling. As a consequence, the divergence of the flow field were over-
all visually higher for the FNH population (insert of 1b) as compared
The authors thank the Laboratory of Excellence TRAIL ANR-10-
LABX-57 for funding. This study has been carried out with the financial
support of the French National Research Agency (ANR) in the frame of the
Investments for the future Programme IdEx Bordeaux-CPU (ANR-10-IDEX-
03-02).
to the I-HCA population (insert of 1d). Over the three tested image-
based transport indicators, only the divergence indicator led to a
significant difference (p-value of Mann-Whitney test= 2.10−7). Di-
agnostic performances of the divergence indicator: accuracy=93.5%,
AUROC=0.93, sensitivity=91.0%, specificity=95.4%, PPV=92.2%,
NPV=95.3% (Naı¨ve Bayes classifier).
Fig. 1. Typical results obtained for FNH and I-HCA lesions.
3. CONCLUSION
This proof-of-concept study indicates that image-based apparent mi-
crobubble transport fields can provide new efficient diagnosis in-
dicators on DCEUS. Machine learning algorithms applied on the
latter provides valuable information for the automatic diagnosis of
FNH/I-HCA lesions. Future study will concern the optimization of
the model, with the study of larger cohorts, the inclusion of other
categories of features and the study of other pathologies.
4. REFERENCES
[1] F. Tranquart et al., “Perfusion quantification in contrast-
enhanced ultrasound (CEUS)–ready for research projects and
routine clinical use,” Ultrash Med, vol. 33, pp. S31–8, 2012.
[2] B. Denis de Senneville et al., “Development of a fluid dynamic
model for quantitative contrast-enhanced ultrasound imaging,”
IEEE Trans on Med Im, vol. 37, no. 2, pp. 372–383, 2018.


Hepatic tumor diagnosis by analysing dense transport fields in contrast-enhanced ultrasound

Denis de Senneville, Baudouin

INRIA a CCSD electronic archive server

HAL Id: hal-02377660https://hal.archives-ouvertes.fr/hal-02377660Submitted on 24 Nov 2019HAL is a multi-disciplinary open accessarchive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come fromteaching and research institutions in France orabroad, or from public or private research centers.L’archive ouverte pluridisciplinaire HAL, estdestinée au dépôt et à la diffusion de documentsscientifiques de niveau recherche, publiés ou non,émanant des établissements d’enseignement et derecherche français ou étrangers, des laboratoirespublics ou privés.Hepatic tumor diagnosis by analysing dense transportfields in contrast-enhanced ultrasoundBaudouin Denis de Senneville, Nora Frulio, Hervé Laumonier, Cécile Salut,Luc Lafitte, Hervé TrillaudTo cite this version:Baudouin Denis de Senneville, Nora Frulio, Hervé Laumonier, Cécile Salut, Luc Lafitte, et al.. Hepatictumor diagnosis by analysing dense transport fields in contrast-enhanced ultrasound. ISBI19 - 16thIEEE International Symposium on Biomedical Imaging, Apr 2019, Venise, Italy. ￿hal-02377660￿HEPATIC TUMOR DIAGNOSIS BY ANALYSING DENSE TRANSPORT FIELDS INCONTRAST-ENHANCED ULTRASOUNDB. Denis de Senneville? N. Frulio† H. Laumonier† C. Salut† L. Lafitte? H. Trillaud†,‡? Mathematical Institute of Bordeaux, UMR 5251 CNRS/University of Bordeaux/INRIA, France† Department of Diagnostic and Interventional Imaging, Hôpital Saint-André,Centre Hospitalier Universitaire de Bordeaux, †IMOTION, University of BordeauxABSTRACTDynamic contrast agent enhanced ultrasound (DCEUS) is con-sidered as a safe, noninvasive, accurate, and economic tool foranalysing blood perfusion of various organs [1]. Gas-filled mi-crobubble contrast agents are used as intravascular flow tracers.In this study, a new methodology is proposed to quantify the di-vergence (i.e sources, sinks), curl (i.e sheering) and amplitude inthe apparent microbubble transports during the bolus arrival. Theefficiency of proposed methodology is evaluated in-vivo, for theclassification of focal nodular hyperplasia (FNH) and inflammatoryhepatic adenomas (I-HCA).1. INTRODUCTIONThe diagnosis between FNH and I-HCA is sometime difficult atDCEUS because both demonstrate a hyper-enhancing at the arterialphase with difficulties to differentiate the centrifugal or centripetalfilling of the tumor with only qualitative visual analysis.Recent efforts in DCEUS aim at quantifying parameters relatedto the ultrasound contrast enhancement in the vascular compartmentand at using these latter as indicators for several pathological condi-tions. In particular, quantitative analysis with the use of a transportequation has been recently introduced to estimate the apparent mi-crobubble velocity of the bolus arrival [2]. In the current study, wepropose a new methodology designed to quantify the divergence (i.esources, sinks), curl (i.e sheering) and amplitude in the estimatedapparent dense transport field. The latter provide three very simpleindicators of displacement vector directions, orientations and mag-nitude, which are used as inputs of a binary FNH/I-HCA classifier.2. RESULTS46 patients with FNH (n=29) or I-HCA (n=17) were analyzed(histological diagnosis). Fig. 1 reports typical estimated microbub-ble transport fields obtained for two DCEUS experiment (upperrow=FNH/ bottom row=I-HCA) 0.75 s after the microbubble arrivaltime. The apparent flow field in 1b shows a fast centrifugal fillingof the lesion from a central vessel and radial vascular branches. Onthe contrary, 1d shows a hyper-enhancing in the arterial phase withan enhancement pattern beginning peripherally, with fast centripetalfilling. As a consequence, the divergence of the flow field were over-all visually higher for the FNH population (insert of 1b) as comparedThe authors thank the Laboratory of Excellence TRAIL ANR-10-LABX-57 for funding. This study has been carried out with the financialsupport of the French National Research Agency (ANR) in the frame of theInvestments for the future Programme IdEx Bordeaux-CPU (ANR-10-IDEX-03-02).to the I-HCA population (insert of 1d). Over the three tested image-based transport indicators, only the divergence indicator led to asignificant difference (p-value of Mann-Whitney test= 2.10−7). Di-agnostic performances of the divergence indicator: accuracy=93.5%,AUROC=0.93, sensitivity=91.0%, specificity=95.4%, PPV=92.2%,NPV=95.3% (Naı̈ve Bayes classifier).Fig. 1. Typical results obtained for FNH and I-HCA lesions.3. CONCLUSIONThis proof-of-concept study indicates that image-based apparent mi-crobubble transport fields can provide new efficient diagnosis in-dicators on DCEUS. Machine learning algorithms applied on thelatter provides valuable information for the automatic diagnosis ofFNH/I-HCA lesions. Future study will concern the optimization ofthe model, with the study of larger cohorts, the inclusion of othercategories of features and the study of other pathologies.4. REFERENCES[1] F. Tranquart et al., “Perfusion quantification in contrast-enhanced ultrasound (CEUS)–ready for research projects androutine clinical use,” Ultrash Med, vol. 33, pp. S31–8, 2012.[2] B. Denis de Senneville et al., “Development of a fluid dynamicmodel for quantitative contrast-enhanced ultrasound imaging,”IEEE Trans on Med Im, vol. 37, no. 2, pp. 372–383, 2018.

Dynamic contrast agent enhanced ultrasound (DCEUS) is considered as a safe, noninvasive, accurate, and economic tool for analysing blood perfusion of various organs [1]. Gas-filled mi-crobubble contrast agents are used as intravascular flow tracers. In this study, a new methodology is proposed to quantify the divergence (i.e sources, sinks), curl (i.e sheering) and amplitude in the apparent microbubble transports during the bolus arrival. The efficiency of proposed methodology is evaluated in-vivo, for the classification of focal nodular hyperplasia (FNH) and inflammatory hepatic adenomas (I-HCA)

Hepatic tumor diagnosis by analysing dense transport fields in contrast-enhanced ultrasound

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